Loading…
Estimation of Tire Load and Vehicle Parameters Using Intelligent Tires Combined With Vehicle Dynamics
This article focuses on the estimation of static/ dynamic tire load and vehicle parameters using intelligent tires and vehicle dynamics. This study is conducted to improve and ensure the performance of advanced vehicle control using accurate vehicle and tire states. The contact angle between tire an...
Saved in:
Published in: | IEEE transactions on instrumentation and measurement 2021, Vol.70, p.1-12 |
---|---|
Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c291t-c8967b2b2dae4757cd55f109d7431b01c18e2d5a59a5e765c95a7afcc714321b3 |
---|---|
cites | cdi_FETCH-LOGICAL-c291t-c8967b2b2dae4757cd55f109d7431b01c18e2d5a59a5e765c95a7afcc714321b3 |
container_end_page | 12 |
container_issue | |
container_start_page | 1 |
container_title | IEEE transactions on instrumentation and measurement |
container_volume | 70 |
creator | Jeong, Dasol Kim, Seungtaek Lee, Jonghyup Choi, Seibum B. Kim, Mintae Lee, Hojong |
description | This article focuses on the estimation of static/ dynamic tire load and vehicle parameters using intelligent tires and vehicle dynamics. This study is conducted to improve and ensure the performance of advanced vehicle control using accurate vehicle and tire states. The contact angle between tire and road surface is calculated by an intelligent tire and is used for tire load estimation. The tire load estimation results are validated by the flexible ring tire model. For a fast sampling rate and high robustness, a new estimation algorithm, which combines intelligent tire and vehicle dynamics, is proposed in this article. Not only the tire load but also the vehicle parameters, such as total mass, center of gravity point (CG point), and center of gravity height (CG height), are estimated by the proposed estimation algorithm. The proposed estimation algorithm is verified by an indoor test using Flac trac (tire test system) and a real-time test using AutoBox III. In short, the estimation algorithm proposed in this article can estimate static/dynamic tire load and vehicle parameters with a fast sampling rate and high robustness. |
doi_str_mv | 10.1109/TIM.2020.3031124 |
format | article |
fullrecord | <record><control><sourceid>proquest_ieee_</sourceid><recordid>TN_cdi_ieee_primary_9223672</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9223672</ieee_id><sourcerecordid>2474855966</sourcerecordid><originalsourceid>FETCH-LOGICAL-c291t-c8967b2b2dae4757cd55f109d7431b01c18e2d5a59a5e765c95a7afcc714321b3</originalsourceid><addsrcrecordid>eNo9kEFPwjAUgBujiYjeTbw08Txsu3ZdjwZRSTB6AD02XfcGJazDthz49w4hnN7l-97L-xC6p2REKVFP8-nHiBFGRjnJKWX8Ag2oEDJTRcEu0YAQWmaKi-Ia3cS4JoTIgssBgklMrjXJdR53DZ67AHjWmRobX-NvWDm7AfxlgmkhQYh4EZ1f4qlPsNm4Jfj0r0Q87trKeajxj0urs_iy96Z1Nt6iq8ZsItyd5hAtXifz8Xs2-3ybjp9nmWWKpsyWqpAVq1htgEshbS1E0z9XS57TilBLS2C1MEIZAbIQVgkjTWOtpDxntMqH6PG4dxu63x3EpNfdLvj-pGZc8lKIPkdPkSNlQxdjgEZvQ98g7DUl-hBT9zH1IaY-xeyVh6PiAOCMK8byQrL8DyIOb_Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2474855966</pqid></control><display><type>article</type><title>Estimation of Tire Load and Vehicle Parameters Using Intelligent Tires Combined With Vehicle Dynamics</title><source>IEEE Electronic Library (IEL) Journals</source><creator>Jeong, Dasol ; Kim, Seungtaek ; Lee, Jonghyup ; Choi, Seibum B. ; Kim, Mintae ; Lee, Hojong</creator><creatorcontrib>Jeong, Dasol ; Kim, Seungtaek ; Lee, Jonghyup ; Choi, Seibum B. ; Kim, Mintae ; Lee, Hojong</creatorcontrib><description>This article focuses on the estimation of static/ dynamic tire load and vehicle parameters using intelligent tires and vehicle dynamics. This study is conducted to improve and ensure the performance of advanced vehicle control using accurate vehicle and tire states. The contact angle between tire and road surface is calculated by an intelligent tire and is used for tire load estimation. The tire load estimation results are validated by the flexible ring tire model. For a fast sampling rate and high robustness, a new estimation algorithm, which combines intelligent tire and vehicle dynamics, is proposed in this article. Not only the tire load but also the vehicle parameters, such as total mass, center of gravity point (CG point), and center of gravity height (CG height), are estimated by the proposed estimation algorithm. The proposed estimation algorithm is verified by an indoor test using Flac trac (tire test system) and a real-time test using AutoBox III. In short, the estimation algorithm proposed in this article can estimate static/dynamic tire load and vehicle parameters with a fast sampling rate and high robustness.</description><identifier>ISSN: 0018-9456</identifier><identifier>EISSN: 1557-9662</identifier><identifier>DOI: 10.1109/TIM.2020.3031124</identifier><identifier>CODEN: IEIMAO</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Center of gravity ; Contact angle ; Estimation ; Flexible ring tire model ; Gravity ; Heuristic algorithms ; intelligent tires ; Load modeling ; load transfer ; Mirrors ; multi-input multi-output (MIMO) system ; Parameters ; Roads ; Robustness ; Sampling ; tire load ; Tires ; Vehicle dynamics ; vehicle parameter</subject><ispartof>IEEE transactions on instrumentation and measurement, 2021, Vol.70, p.1-12</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-c8967b2b2dae4757cd55f109d7431b01c18e2d5a59a5e765c95a7afcc714321b3</citedby><cites>FETCH-LOGICAL-c291t-c8967b2b2dae4757cd55f109d7431b01c18e2d5a59a5e765c95a7afcc714321b3</cites><orcidid>0000-0002-0206-5401 ; 0000000303291184 ; 0000-0002-1022-5129 ; 0000-0002-8555-4429 ; 0000-0001-8412-9458 ; 0000-0001-8517-1244 ; 0000-0003-0329-1184</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9223672$$EHTML$$P50$$Gieee$$H</linktohtml></links><search><creatorcontrib>Jeong, Dasol</creatorcontrib><creatorcontrib>Kim, Seungtaek</creatorcontrib><creatorcontrib>Lee, Jonghyup</creatorcontrib><creatorcontrib>Choi, Seibum B.</creatorcontrib><creatorcontrib>Kim, Mintae</creatorcontrib><creatorcontrib>Lee, Hojong</creatorcontrib><title>Estimation of Tire Load and Vehicle Parameters Using Intelligent Tires Combined With Vehicle Dynamics</title><title>IEEE transactions on instrumentation and measurement</title><addtitle>TIM</addtitle><description>This article focuses on the estimation of static/ dynamic tire load and vehicle parameters using intelligent tires and vehicle dynamics. This study is conducted to improve and ensure the performance of advanced vehicle control using accurate vehicle and tire states. The contact angle between tire and road surface is calculated by an intelligent tire and is used for tire load estimation. The tire load estimation results are validated by the flexible ring tire model. For a fast sampling rate and high robustness, a new estimation algorithm, which combines intelligent tire and vehicle dynamics, is proposed in this article. Not only the tire load but also the vehicle parameters, such as total mass, center of gravity point (CG point), and center of gravity height (CG height), are estimated by the proposed estimation algorithm. The proposed estimation algorithm is verified by an indoor test using Flac trac (tire test system) and a real-time test using AutoBox III. In short, the estimation algorithm proposed in this article can estimate static/dynamic tire load and vehicle parameters with a fast sampling rate and high robustness.</description><subject>Algorithms</subject><subject>Center of gravity</subject><subject>Contact angle</subject><subject>Estimation</subject><subject>Flexible ring tire model</subject><subject>Gravity</subject><subject>Heuristic algorithms</subject><subject>intelligent tires</subject><subject>Load modeling</subject><subject>load transfer</subject><subject>Mirrors</subject><subject>multi-input multi-output (MIMO) system</subject><subject>Parameters</subject><subject>Roads</subject><subject>Robustness</subject><subject>Sampling</subject><subject>tire load</subject><subject>Tires</subject><subject>Vehicle dynamics</subject><subject>vehicle parameter</subject><issn>0018-9456</issn><issn>1557-9662</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNo9kEFPwjAUgBujiYjeTbw08Txsu3ZdjwZRSTB6AD02XfcGJazDthz49w4hnN7l-97L-xC6p2REKVFP8-nHiBFGRjnJKWX8Ag2oEDJTRcEu0YAQWmaKi-Ia3cS4JoTIgssBgklMrjXJdR53DZ67AHjWmRobX-NvWDm7AfxlgmkhQYh4EZ1f4qlPsNm4Jfj0r0Q87trKeajxj0urs_iy96Z1Nt6iq8ZsItyd5hAtXifz8Xs2-3ybjp9nmWWKpsyWqpAVq1htgEshbS1E0z9XS57TilBLS2C1MEIZAbIQVgkjTWOtpDxntMqH6PG4dxu63x3EpNfdLvj-pGZc8lKIPkdPkSNlQxdjgEZvQ98g7DUl-hBT9zH1IaY-xeyVh6PiAOCMK8byQrL8DyIOb_Q</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Jeong, Dasol</creator><creator>Kim, Seungtaek</creator><creator>Lee, Jonghyup</creator><creator>Choi, Seibum B.</creator><creator>Kim, Mintae</creator><creator>Lee, Hojong</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-0206-5401</orcidid><orcidid>https://orcid.org/0000000303291184</orcidid><orcidid>https://orcid.org/0000-0002-1022-5129</orcidid><orcidid>https://orcid.org/0000-0002-8555-4429</orcidid><orcidid>https://orcid.org/0000-0001-8412-9458</orcidid><orcidid>https://orcid.org/0000-0001-8517-1244</orcidid><orcidid>https://orcid.org/0000-0003-0329-1184</orcidid></search><sort><creationdate>2021</creationdate><title>Estimation of Tire Load and Vehicle Parameters Using Intelligent Tires Combined With Vehicle Dynamics</title><author>Jeong, Dasol ; Kim, Seungtaek ; Lee, Jonghyup ; Choi, Seibum B. ; Kim, Mintae ; Lee, Hojong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-c8967b2b2dae4757cd55f109d7431b01c18e2d5a59a5e765c95a7afcc714321b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Center of gravity</topic><topic>Contact angle</topic><topic>Estimation</topic><topic>Flexible ring tire model</topic><topic>Gravity</topic><topic>Heuristic algorithms</topic><topic>intelligent tires</topic><topic>Load modeling</topic><topic>load transfer</topic><topic>Mirrors</topic><topic>multi-input multi-output (MIMO) system</topic><topic>Parameters</topic><topic>Roads</topic><topic>Robustness</topic><topic>Sampling</topic><topic>tire load</topic><topic>Tires</topic><topic>Vehicle dynamics</topic><topic>vehicle parameter</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jeong, Dasol</creatorcontrib><creatorcontrib>Kim, Seungtaek</creatorcontrib><creatorcontrib>Lee, Jonghyup</creatorcontrib><creatorcontrib>Choi, Seibum B.</creatorcontrib><creatorcontrib>Kim, Mintae</creatorcontrib><creatorcontrib>Lee, Hojong</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005–Present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998–Present</collection><collection>IEEE Xplore</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on instrumentation and measurement</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jeong, Dasol</au><au>Kim, Seungtaek</au><au>Lee, Jonghyup</au><au>Choi, Seibum B.</au><au>Kim, Mintae</au><au>Lee, Hojong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimation of Tire Load and Vehicle Parameters Using Intelligent Tires Combined With Vehicle Dynamics</atitle><jtitle>IEEE transactions on instrumentation and measurement</jtitle><stitle>TIM</stitle><date>2021</date><risdate>2021</risdate><volume>70</volume><spage>1</spage><epage>12</epage><pages>1-12</pages><issn>0018-9456</issn><eissn>1557-9662</eissn><coden>IEIMAO</coden><abstract>This article focuses on the estimation of static/ dynamic tire load and vehicle parameters using intelligent tires and vehicle dynamics. This study is conducted to improve and ensure the performance of advanced vehicle control using accurate vehicle and tire states. The contact angle between tire and road surface is calculated by an intelligent tire and is used for tire load estimation. The tire load estimation results are validated by the flexible ring tire model. For a fast sampling rate and high robustness, a new estimation algorithm, which combines intelligent tire and vehicle dynamics, is proposed in this article. Not only the tire load but also the vehicle parameters, such as total mass, center of gravity point (CG point), and center of gravity height (CG height), are estimated by the proposed estimation algorithm. The proposed estimation algorithm is verified by an indoor test using Flac trac (tire test system) and a real-time test using AutoBox III. In short, the estimation algorithm proposed in this article can estimate static/dynamic tire load and vehicle parameters with a fast sampling rate and high robustness.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIM.2020.3031124</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-0206-5401</orcidid><orcidid>https://orcid.org/0000000303291184</orcidid><orcidid>https://orcid.org/0000-0002-1022-5129</orcidid><orcidid>https://orcid.org/0000-0002-8555-4429</orcidid><orcidid>https://orcid.org/0000-0001-8412-9458</orcidid><orcidid>https://orcid.org/0000-0001-8517-1244</orcidid><orcidid>https://orcid.org/0000-0003-0329-1184</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0018-9456 |
ispartof | IEEE transactions on instrumentation and measurement, 2021, Vol.70, p.1-12 |
issn | 0018-9456 1557-9662 |
language | eng |
recordid | cdi_ieee_primary_9223672 |
source | IEEE Electronic Library (IEL) Journals |
subjects | Algorithms Center of gravity Contact angle Estimation Flexible ring tire model Gravity Heuristic algorithms intelligent tires Load modeling load transfer Mirrors multi-input multi-output (MIMO) system Parameters Roads Robustness Sampling tire load Tires Vehicle dynamics vehicle parameter |
title | Estimation of Tire Load and Vehicle Parameters Using Intelligent Tires Combined With Vehicle Dynamics |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-03-09T06%3A45%3A46IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_ieee_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Estimation%20of%20Tire%20Load%20and%20Vehicle%20Parameters%20Using%20Intelligent%20Tires%20Combined%20With%20Vehicle%20Dynamics&rft.jtitle=IEEE%20transactions%20on%20instrumentation%20and%20measurement&rft.au=Jeong,%20Dasol&rft.date=2021&rft.volume=70&rft.spage=1&rft.epage=12&rft.pages=1-12&rft.issn=0018-9456&rft.eissn=1557-9662&rft.coden=IEIMAO&rft_id=info:doi/10.1109/TIM.2020.3031124&rft_dat=%3Cproquest_ieee_%3E2474855966%3C/proquest_ieee_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c291t-c8967b2b2dae4757cd55f109d7431b01c18e2d5a59a5e765c95a7afcc714321b3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2474855966&rft_id=info:pmid/&rft_ieee_id=9223672&rfr_iscdi=true |